Irc, Cva and Var – New Methods in Basel Essay
Irc, Cva and Var – New Methods in Basel
Last financial crisis was seen as a strong slap on the global economy. It has awakened Basel Committee on Banking Supervision (BCBS) about the importance of an aggregation between market and credit risks that banks have to cope with. In accordance with Saunders and Cornett (2011), definition of market risk is “the risk related to the uncertainty of an FI’s (financial institution) earnings on its trading portfolio caused by changes, and particularly extreme changes, in market conditions”. Interest rate risk and foreign exchange risk are some typical example for market risks (Saunders and Cornett, 2011). Meanwhile, credit risk is defined as risk increased when borrowers, bond issuers and counterparties in derivatives transaction may default (Hull, 2010).
According to Madigan (2010), it would be greater risks when credit and market risks associated than the sum of individual factors. Therefore, it might lead to worse impacts to banks’ operations. From the crisis’s consequences, Nout Wellink – chairman of the Basel Committee believes that it is necessary for supervisors to learn experiences from recent events, thus set up new methods for banks to cope with fore problems (Ferry, 2008). These new rules which are reflected in Basel III support each other to efficiently measure and manage correlated risks, thus calculate capital requirement to cover these risks. A report by Goeth (2010) defines Basel III as an extensive set of measures reformed in order to enhance the regulation, supervision and risk management in terms of banking.
This report mentions new methods with their strengths, weaknesses and effectiveness to help banks control and measure risks effectively, especially combination of credit and market risks. They are incremental risk charge (IRC), credit valuation adjustment (CVA) and stresses value at risk (VAR) model.
II. Incremental Risk Charge – IRC
1. Strengths of Incremental Risk Charge Model
In order to avoid crisis, banks must satisfy capital requirement demanded by Basel Committee to cover individual as well as correlated risks. IRC is a method which helps banks to estimate minimum capital needed to cover risks from unsecuritised credit instruments caused by default and migration events (BCBS, 2009b). It means IRC model calculates the maximum risks in the worst case when banks cannot securitise any products. As a result, banks have to set up the suitable capital for their own business and make sure that they can overcome difficulties even in the worst situation. In other words, banks will be safe from default and migration events, and more importantly, they can avoid crisis by using IRC model.
In Basel III, with IRC model, risks can be measured for a one-year capital horizon at 99.9% confidence level, instead of a 10-day VAR at the 99% confidence level as in Basel II (Davidson, 2009). The extension of capital horizon is one of IRC’s strengths because it can evaluate and calculate banks’ risks more effectively and accurately than 10-day VAR. The reason is one-day or 10-day VAR cannot comprise completely large cumulative price variation occurring several weeks or months as well as large daily losses which only happen two or three times per year (BCBS, 2009b). As a result, one-year horizon is the optimal time for banks to rebalance their capital. 2. Weaknesses of Incremental Risk Charge Model
Under BCBS’s approval, banks are expected to improve their own IRC models to calculate risks for individual positions or sets of positions (BCBS, 2009b). It means the Committee hopes banks will have their own choice of liquidity horizon which is appropriate with their business without any issued industry benchmarks or standards (Stretton, 2011). However, it leads to inconsistence within banking system. Furthermore, supervisors have to face with more difficulties in process of evaluating banks’ IRC model.
Although IRC helps bank to capture risks more effectively, especially when market and credit risks collide, there is a significant weakness still be existing. It is the overlap of counterparty credit risk cooperated with over the counters (OTC) and repo-style transactions between IRC and CVA (Stretton, 2011). As a consequence, it will lead to duplicate capital charge for the banks. Suggested by Linsz (2010) – the corporate Treasurer of Bank of America, the Committee should apply an integrated approach to combine the overlapping risks by deleting the risk above in IRC model, hence build up more accurate capital charge for banks. In fact, Bank of America thinks duplicated capital charge is inappropriate with risk management practices (Linsz, 2010). 3. Effectiveness of Incremental Risk Charge Model
According to BCBS (2009b), IRC model mainly compounds two types of risks: default risk and credit migration risk. The origin of default risks can be obligors’ default and/or default events. As a result, it may lead to direct losses and/or indirect losses respectively. Meanwhile, credit migration risks may come from internal or external rating downgrade or upgrade as well as credit migration events (BCBS, 2009b).
A study by Kealhofer et al. (1998) and Kealhofer (2003) (cited in Varotto, 2011), there are two main methods applied to rate company’s performance which are Through The Cycle (TTC) rating and Point In Time (PIT) rating. Both two rating methods are used to evaluate repay ability of a business, thus bank sets up its own capital to cover risks in case of the business’s default. Nevertheless, there are several differences between TTC and PIT ratings are as follows. While TTC rating tries to achieve stable rating which is not influenced by economic variation over mid-term or long-term, PIT rating reflects changes of the market as well as credit migration through the credit rating in a short-term. A study by Benford and Nier (2007) found that banks prefer to use PIT rating because it can update market variations and reflect them through enterprise’s credit rating downgrade or upgrade more effectively. In other words, IRC model which is used to estimate capital requirement for banks based on their risks is influenced by both credit and market risks.
III. Credit Valuation Adjustment (CVA)
1. Strengths of Credit Valuation Adjustment
A capital charge for credit valuation adjustment (CVA) is a procedure used to calculate capital requirement for mark to market losses associated with counterparties’ decreased creditworthiness (BCBS, 2011b). Compare with the traditional method, CVA is more dynamic because it allows a bank or a financial institution to have trading opportunities with large exposures that excel limits set up to oppose future risks – the thing that the traditional method does not permit (Algorithmics, 2009). In fact, based on high risk, high return theory, banks have chance to increase their profit by the trading opportunities as above. Therefore, applying CVA approach instead of the traditional one may help banks achieve much profit.
2. Weaknesses of Credit Valuation Adjustment
When banks apply CVA approach, they have to face with a difficulty which is seen as weakness of CVA. It is banks cannot identify and evaluate counterparty’s credit rating accurately (Cameron, 2011). One of the reasons of this disadvantage is derivatives which are originally purchased between bank and counterparty can be transferred to the third party, then fourth party and so on… As a consequence, the bank cannot control its counterparties effectively, thus it will lead to bank’s incorrect rating counterparty. Another reason might be mistakes of rating agencies because they do not have enough information about banks’ counterparty. Therefore, it will cause inaccurate risk measure when applying CVA approach.
In addition, a report undertaken in this area (Cameron, 2011) shows that there are some participants found CVA’s structuring is sophisticated to apply in several real situations. The dealer proves that there still be existing a lot of pitfalls and problems through the calculating risk process. As a consequence, it might lead to many difficulties for banks in using CVA.
3. Effectiveness of Credit Valuation Adjustment
A study by Barus et al. (2010) found that CVA approach uses one-year market risk horizon instead of 10-day. It is the same horizon with model as well as VAR models; therefore it helps banks manage risks easier based on integrated time horizon between risks controlling models.
In addition, BCBS (2011b) states that CVA capital charge includes charge for mark to market losses and counterparty’s devaluation in creditworthiness. If banks purchase securities at current time, then their market price decreases, banks will take an expenditure called mark to market losses. CVA captures these risks above means it covers market risk might occur to the banks. In fact, within the last crisis, only one-third of counterparty credit risks were due to actual defaults while the remaining two-thirds caused by CVA losses, especially mark-to-market losses (Goeth, 2010).
As mentioned above, CVA also captures risk of counterparty’s devaluation in creditworthiness. According to BCBS (2011a), creditworthiness mentions ability to repay or meet debt obligation of an individual or an enterprise. Therefore, when the counterparty’s repay ability deteriorates, it will lead to increasing of CVA capital charge for banks (Bushnell, 2007) in order to help banks prepare an adequate capital. Put differently, CVA not only captures market risks but also cover credit risks that banks have to face with. As a result, CVA and IRC model associate and support each other to help banks measure and manage combination of market and credit risks more completely effectively.
IV. Stressed VAR
1. Strengths of Stressed VAR Model
According to Butler (1999), VAR is defined as calculation used to measure “the worst expected loss that an institution can suffer over a given time interval under normal market conditions at a given confidence level.” After the crisis in the year 2007, Basel Committee realised that market condition is not always consistent. Therefore, stressed VAR was created to compute VAR which would be performed on the present portfolio of a bank in case that the related market elements were going through a stressed period (BCBS, 2009a).
Based on VAR calculated, banks are required to have an appropriate amount of capital to cover their worst expected loss. One of VAR charge’s strengths is it reduces the pro-cyclical capital which are disadvantages for the banks. As stated by Christopher Finger (cited in Pengelly, 2011), recent data used for calculating VAR moved around and around, and it might lead to bad aggregation of more volatile markets, dealers’ losses and enlarged capital.
2. Weaknesses of Stressed VAR Model
The weaknesses that can be easily seen in stressed VAR model is stressed VAR cannot capture migration and default risks of banks. That is the reason why banks also have to apply IRC model to capture these risks. Furthermore, stressed VAR also cannot cover mark-to-market losses which need to be measured by CVA approach. Therefore, banks have to cope with more complexity in risk measure; as a consequence, banks can make more mistakes in calculating risk process. One more important point is stressed VAR is not able to measure risk in a normal market condition, thus banks need to use one more different model – normal VAR calculation to measure this type of risk. Consequently, it will require really careful and complicated risk management system in order to measure risk accurately.
3. Effectiveness of Stressed VAR Model
In accordance with BCBS (2011c), the effectiveness of stressed VAR model is performed through it can include all risks, for instance interest rate risk, commodity risk, etc. over a period of stressed market that banks recently experienced. In other words, the more types of risks stressed VAR can cover, the more accurately banks can measure and manage risks.
From the stressed VAR’s definition mentioned above, BCBS suggested that “it should be based on the 10-day, 99th percentile, one-tailed confidence interval VAR measure of the current portfolio, with model inputs calibrated to historical data from a continuous 12-month period of significant financial stress relevant to the bank’s portfolio.” It means stressed VAR uses the same time horizon with IRC and CVA in order to help banks reduce mistakes in risk calculating process due to united horizon. Concurrently, the same time horizon also assists supervisors to revise banks’ risks more effectively. Besides, in order to set up an effective risk management method, banks have to use time-series data of 12-continuous-month for stressed VAR model that includes financial stress event which is relevant to banks’ portfolio (BCBS, 2011c). As a result, the financial crisis from 2007 to 2009 is the time period suggested by the Committee to banks to be used for building stressed VAR model.
In Basel III, three new methods above – Incremental Risk Charge, Capital Valuation Adjustment and Stressed Value at Risk – are concurrently used by the banks and they support each other to measure and manage risks more effectively. Strengths of one method are supplementary for others’ weaknesses. That is the reason why banks are required by Basel Committee to add both of three methods into their risk management. With normal VAR model, IRC, CVA and stressed VAR approaches help banks not only control risks as individual factors but also measure and manage risks as a combination, especially the aggregation of credit and market risks more efficiently. From that, banks need to set up their own capital which is appropriate with their financial situation in order to face with difficulties that the financial crisis 2007-2009 was the typical example.
Besides undeniable advantages of three new rules, the largest banks in the world, such as Bank of America, UBS, Royal Bank of Scotland, still found significant weaknesses and gave comment on the Basel Committee on Banking Supervision’s consultative documents. Basel Committee should concern about these recommendations to readjust Basel III in order to set up an accurate and effective regulation documents for international banks to help banks in particular as well as financial institutions in general avoid disasters as the financial crisis happened in 2007 to 2009.
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University/College: University of California
Type of paper: Thesis/Dissertation Chapter
Date: 13 October 2016
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